Personalized route indices via crowd-sourced data

• US 10,037,695 B2
• Filed: 10/22/2014
• Issued: 07/31/2018
• Est. Priority Date: 10/22/2014
• Status: Active Grant

• Current Assignee: Ford Global Technologies, LLC (Ford Motor Company)
• Original Assignee: Ford Global Technologies, LLC (Ford Motor Company)
• Inventors: D'Amato, Anthony Mario, Michelini, John Ottavio
• Primary Examiner(s): Lin, Abby Yee
• Assistant Examiner(s): Castro, Paul A
• Application Number:
  US14/520,422
• Publication Number:
  US 20160117921A1
• Time in Patent Office: 1,378 Days
• Field of Search: None
• CPC Class Codes: G06F 3/0484 for the control of specific functions or operations, e.g. selecting or manipulating an object, an image or a displayed text element, setting a parameter value or selecting a range
• CPC Class Codes: G07C 5/008 communicating information to a remotely located station transmission systems for measured values G08C
• CPC Class Codes: G08G 1/0112 from the vehicle, e.g. floating car data [FCD]
• CPC Class Codes: G08G 1/0133 for classifying traffic situation
• CPC Class Codes: G08G 1/0141 for traffic information dissemination
• CPC Class Codes: G08G 1/096716 where the received information does not generate an automatic action on the vehicle control
• CPC Class Codes: G08G 1/096741 where the source of the transmitted information selects which information to transmit to each vehicle
• CPC Class Codes: G08G 1/096775 where the origin of the information is a central station

Abstract

Traffic incident information may be clustered to determine geographical locations in which a statistically-increased level of traffic incidents occur. Indices indicative of vehicle operating conditions within the locations may be generated according to crowd-sourced event information factors and an index function including coefficients defining contributions of the factors to the indices. The coefficients may be optimized to minimize error between the index-predicted statistically-increased level areas and the clustered traffic incident information.

Claims

1. A system comprising:

a vehicle processor programmed to

cluster traffic incident information to determine geographical locations in which a statistically-increased level of traffic incidents occur;

generate traffic incident likelihood indices predictive of traffic incidents levels within the geographic locations according to crowd-sourced event information factors and an index function including coefficients defining contributions of the information factors to the traffic incident likelihood indices, the index function being of the form

Ri(k)=f_1(geometry(k),a_1, . . . ,a_n)+f_2(weather(k),a_(n+1), . . . ,a_m)+f_3(crowd data(k),a_(m+1), . . . ,a_l),

where Ri represents the traffic incident likelihood indices, k represents the geographic locations for which the indices Ri are being calculated, f₁ represents a function of road geometry information, f₂ represents a function of weather conditions, f₃ represent a function of the crowd-sourced event information, and a₁, . . . , a_l represent the coefficients defining contributions used to weight the factors in creation of the indices Ri; and

optimize the coefficients to minimize error between the indices Ri and the clustered traffic incident information; and

generate traffic incident likelihood alerts responsive to the traffic incident likelihood indices exceeding a threshold level of traffic incident likelihood.

2. The system of claim 1, wherein the crowd-sourced event information includes at least two of traffic data, environment data, road type data, human factor data, and vehicle parameter data.

3. The system of claim 1, wherein the factors include hard braking events and hard steering events.

4. The system of claim 1, wherein the vehicle processor is further configured to optimize the coefficients according to historical crowd-sourced event information of a specific vehicle driver to determine coefficients configured to generate indices optimized for the driver.

5. The system of claim 1, wherein the traffic incident information further includes traffic incidents identified according to the crowd-sourced event information.

6. The system of claim 1, wherein the vehicle processor is included in an index server device further configured to receive the crowd-sourced event information over a wide area network from a plurality of vehicles.

7. The system of claim 1, wherein the vehicle processor is further configured to:

receive a request for an index for a geographic location from a vehicle; and

provide the index to vehicle according to the index function and coefficients.

8. The system of claim 7, wherein the geographic location is a current geographic area in which the vehicle is located.